refactor: switch group by instead of triggering aggregation

Using FINAL in clickhouse query will trigger the aggregation
merge of data while using group by will be more efficient.
It's recommended id docs as well - https://clickhouse.com/
docs/engines/table-engines/mergetree-family/
aggregatingmergetree#select-and-insert

frontend/src/lib/uPlotV2/utils/__tests__/dataUtils.test.ts

@@ -1,62 +0,0 @@
-import { isInvalidPlotValue, normalizePlotValue } from '../dataUtils';
-
-describe('dataUtils', () => {
-	describe('isInvalidPlotValue', () => {
-		it('treats null and undefined as invalid', () => {
-			expect(isInvalidPlotValue(null)).toBe(true);
-			expect(isInvalidPlotValue(undefined)).toBe(true);
-		});
-
-		it('treats finite numbers as valid and non-finite as invalid', () => {
-			expect(isInvalidPlotValue(0)).toBe(false);
-			expect(isInvalidPlotValue(123.45)).toBe(false);
-			expect(isInvalidPlotValue(Number.NaN)).toBe(true);
-			expect(isInvalidPlotValue(Infinity)).toBe(true);
-			expect(isInvalidPlotValue(-Infinity)).toBe(true);
-		});
-
-		it('treats well-formed numeric strings as valid', () => {
-			expect(isInvalidPlotValue('0')).toBe(false);
-			expect(isInvalidPlotValue('123.45')).toBe(false);
-			expect(isInvalidPlotValue('-1')).toBe(false);
-		});
-
-		it('treats Infinity/NaN string variants and non-numeric strings as invalid', () => {
-			expect(isInvalidPlotValue('+Inf')).toBe(true);
-			expect(isInvalidPlotValue('-Inf')).toBe(true);
-			expect(isInvalidPlotValue('Infinity')).toBe(true);
-			expect(isInvalidPlotValue('-Infinity')).toBe(true);
-			expect(isInvalidPlotValue('NaN')).toBe(true);
-			expect(isInvalidPlotValue('not-a-number')).toBe(true);
-		});
-
-		it('treats non-number, non-string values as valid (left to caller)', () => {
-			expect(isInvalidPlotValue({})).toBe(false);
-			expect(isInvalidPlotValue([])).toBe(false);
-			expect(isInvalidPlotValue(true)).toBe(false);
-		});
-	});
-
-	describe('normalizePlotValue', () => {
-		it('returns null for invalid values detected by isInvalidPlotValue', () => {
-			expect(normalizePlotValue(null)).toBeNull();
-			expect(normalizePlotValue(undefined)).toBeNull();
-			expect(normalizePlotValue(NaN)).toBeNull();
-			expect(normalizePlotValue(Infinity)).toBeNull();
-			expect(normalizePlotValue('-Infinity')).toBeNull();
-			expect(normalizePlotValue('not-a-number')).toBeNull();
-		});
-
-		it('parses valid numeric strings into numbers', () => {
-			expect(normalizePlotValue('0')).toBe(0);
-			expect(normalizePlotValue('123.45')).toBe(123.45);
-			expect(normalizePlotValue('-1')).toBe(-1);
-		});
-
-		it('passes through valid numbers unchanged', () => {
-			expect(normalizePlotValue(0)).toBe(0);
-			expect(normalizePlotValue(123)).toBe(123);
-			expect(normalizePlotValue(42.5)).toBe(42.5);
-		});
-	});
-});

frontend/src/lib/uPlotV2/utils/__tests__/scale.test.ts

@@ -1,201 +0,0 @@
-import uPlot from 'uplot';
-
-import { DistributionType } from '../../config/types';
-import * as scaleUtils from '../scale';
-
-describe('scale utils', () => {
-	describe('normalizeLogScaleLimits', () => {
-		it('returns limits unchanged when distribution is not logarithmic', () => {
-			const limits = {
-				min: 1,
-				max: 100,
-				softMin: 5,
-				softMax: 50,
-			};
-
-			const result = scaleUtils.normalizeLogScaleLimits({
-				distr: DistributionType.Linear,
-				logBase: 10,
-				limits,
-			});
-
-			expect(result).toEqual(limits);
-		});
-
-		it('snaps positive limits to powers of the log base when distribution is logarithmic', () => {
-			const result = scaleUtils.normalizeLogScaleLimits({
-				distr: DistributionType.Logarithmic,
-				logBase: 10,
-				limits: {
-					min: 3,
-					max: 900,
-					softMin: 12,
-					softMax: 85,
-				},
-			});
-
-			expect(result.min).toBe(1); // 10^0
-			expect(result.max).toBe(1000); // 10^3
-			expect(result.softMin).toBe(10); // 10^1
-			expect(result.softMax).toBe(100); // 10^2
-		});
-	});
-
-	describe('getDistributionConfig', () => {
-		it('returns empty config for time scales', () => {
-			const config = scaleUtils.getDistributionConfig({
-				time: true,
-				distr: DistributionType.Linear,
-				logBase: 2,
-			});
-
-			expect(config).toEqual({});
-		});
-
-		it('returns linear distribution settings for non-time scales', () => {
-			const config = scaleUtils.getDistributionConfig({
-				time: false,
-				distr: DistributionType.Linear,
-				logBase: 2,
-			});
-
-			expect(config.distr).toBe(1);
-			expect(config.log).toBe(2);
-		});
-
-		it('returns log distribution settings for non-time scales', () => {
-			const config = scaleUtils.getDistributionConfig({
-				time: false,
-				distr: DistributionType.Logarithmic,
-				logBase: 10,
-			});
-
-			expect(config.distr).toBe(3);
-			expect(config.log).toBe(10);
-		});
-	});
-
-	describe('getRangeConfig', () => {
-		it('computes range config and fixed range flags correctly', () => {
-			const {
-				rangeConfig,
-				hardMinOnly,
-				hardMaxOnly,
-				hasFixedRange,
-			} = scaleUtils.getRangeConfig(0, 100, null, null, 0.1, 0.2);
-
-			expect(rangeConfig.min).toEqual({
-				pad: 0.1,
-				hard: 0,
-				soft: undefined,
-				mode: 3,
-			});
-			expect(rangeConfig.max).toEqual({
-				pad: 0.2,
-				hard: 100,
-				soft: undefined,
-				mode: 3,
-			});
-			expect(hardMinOnly).toBe(true);
-			expect(hardMaxOnly).toBe(true);
-			expect(hasFixedRange).toBe(true);
-		});
-	});
-
-	describe('createRangeFunction', () => {
-		it('returns [dataMin, dataMax] when no fixed range and no data', () => {
-			const params = {
-				rangeConfig: {} as uPlot.Range.Config,
-				hardMinOnly: false,
-				hardMaxOnly: false,
-				hasFixedRange: false,
-				min: null,
-				max: null,
-			};
-
-			const rangeFn = scaleUtils.createRangeFunction(params);
-
-			const u = ({
-				scales: {
-					y: {
-						distr: 1,
-						log: 10,
-					},
-				},
-			} as unknown) as uPlot;
-
-			const result = rangeFn(
-				u,
-				(null as unknown) as number,
-				(null as unknown) as number,
-				'y',
-			);
-
-			expect(result).toEqual([null, null]);
-		});
-
-		it('applies hard min/max for linear scale when only hard limits are set', () => {
-			const params = {
-				rangeConfig: {} as uPlot.Range.Config,
-				hardMinOnly: true,
-				hardMaxOnly: true,
-				hasFixedRange: true,
-				min: 0,
-				max: 100,
-			};
-
-			const rangeFn = scaleUtils.createRangeFunction(params);
-
-			// Use an undefined distr so the range function skips calling uPlot.rangeNum
-			// and we can focus on the behavior of applyHardLimits.
-			const u = ({
-				scales: {
-					y: {
-						distr: undefined,
-						log: 10,
-					},
-				},
-			} as unknown) as uPlot;
-
-			const result = rangeFn(u, 10, 20, 'y');
-
-			// After applyHardLimits, the returned range should respect configured min/max
-			expect(result).toEqual([0, 100]);
-		});
-	});
-
-	describe('adjustSoftLimitsWithThresholds', () => {
-		it('returns original soft limits when there are no thresholds', () => {
-			const result = scaleUtils.adjustSoftLimitsWithThresholds(1, 5, [], 'ms');
-
-			expect(result).toEqual({ softMin: 1, softMax: 5 });
-		});
-
-		it('expands soft limits to include threshold min/max values', () => {
-			const result = scaleUtils.adjustSoftLimitsWithThresholds(
-				3,
-				6,
-				[{ thresholdValue: 2 }, { thresholdValue: 8 }],
-				'ms',
-			);
-
-			// min should be pulled down to the smallest threshold value
-			expect(result.softMin).toBe(2);
-			// max should be pushed up to the largest threshold value
-			expect(result.softMax).toBe(8);
-		});
-	});
-
-	describe('getFallbackMinMaxTimeStamp', () => {
-		it('returns a 24-hour window ending at approximately now', () => {
-			const { fallbackMin, fallbackMax } = scaleUtils.getFallbackMinMaxTimeStamp();
-
-			// Difference should be exactly one day in seconds
-			expect(fallbackMax - fallbackMin).toBe(86400);
-
-			// Both should be reasonable timestamps (not NaN or negative)
-			expect(fallbackMin).toBeGreaterThan(0);
-			expect(fallbackMax).toBeGreaterThan(fallbackMin);
-		});
-	});
-});

frontend/src/lib/uPlotV2/utils/__tests__/threshold.test.ts

@@ -1,36 +0,0 @@
-import { findMinMaxThresholdValues } from '../threshold';
-
-describe('findMinMaxThresholdValues', () => {
-	it('returns [null, null] when thresholds array is empty or missing', () => {
-		expect(findMinMaxThresholdValues([], 'ms')).toEqual([null, null]);
-		// @ts-expect-error intentional undefined to cover defensive branch
-		expect(findMinMaxThresholdValues(undefined, 'ms')).toEqual([null, null]);
-	});
-
-	it('returns min and max from thresholdValue when units are not provided', () => {
-		const thresholds = [
-			{ thresholdValue: 5 },
-			{ thresholdValue: 1 },
-			{ thresholdValue: 10 },
-		];
-
-		const [min, max] = findMinMaxThresholdValues(thresholds);
-
-		expect(min).toBe(1);
-		expect(max).toBe(10);
-	});
-
-	it('ignores thresholds without a value or with unconvertible units', () => {
-		const thresholds = [
-			// Should be ignored: convertValue returns null for unknown unit
-			{ thresholdValue: 100, thresholdUnit: 'unknown-unit' },
-			// Should be used
-			{ thresholdValue: 4 },
-		];
-
-		const [min, max] = findMinMaxThresholdValues(thresholds, 'ms');
-
-		expect(min).toBe(4);
-		expect(max).toBe(4);
-	});
-});

pkg/query-service/app/clickhouseReader/reader.go

@@ -830,7 +830,7 @@ func (r *ClickHouseReader) GetUsage(ctx context.Context, queryParams *model.GetU
 
 func (r *ClickHouseReader) GetSpansForTrace(ctx context.Context, traceID string, traceDetailsQuery string) ([]model.SpanItemV2, *model.ApiError) {
 	var traceSummary model.TraceSummary
-	summaryQuery := fmt.Sprintf("SELECT * from %s.%s FINAL WHERE trace_id=$1", r.TraceDB, r.traceSummaryTable)
+	summaryQuery := fmt.Sprintf("SELECT trace_id, min(start) AS start, max(end) AS end, sum(num_spans) AS num_spans FROM %s.%s WHERE trace_id=$1 GROUP BY trace_id", r.TraceDB, r.traceSummaryTable)
 	err := r.db.QueryRow(ctx, summaryQuery, traceID).Scan(&traceSummary.TraceID, &traceSummary.Start, &traceSummary.End, &traceSummary.NumSpans)
 	if err != nil {
 		if err == sql.ErrNoRows {
@@ -6458,7 +6458,7 @@ func (r *ClickHouseReader) SearchTraces(ctx context.Context, params *model.Searc
 	}
 
 	var traceSummary model.TraceSummary
-	summaryQuery := fmt.Sprintf("SELECT * from %s.%s FINAL WHERE trace_id=$1", r.TraceDB, r.traceSummaryTable)
+	summaryQuery := fmt.Sprintf("SELECT trace_id, min(start) AS start, max(end) AS end, sum(num_spans) AS num_spans FROM %s.%s WHERE trace_id=$1 GROUP BY trace_id", r.TraceDB, r.traceSummaryTable)
 	err := r.db.QueryRow(ctx, summaryQuery, params.TraceID).Scan(&traceSummary.TraceID, &traceSummary.Start, &traceSummary.End, &traceSummary.NumSpans)
 	if err != nil {
 		if err == sql.ErrNoRows {